观察者与策略

# Python 装饰器
import time
import functools

def log_time(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        print(f"{func.__name__} 耗时 {time.time() - start:.4f}s")
        return result
    return wrapper

def cache(func):                    # 简单结果缓存
    _cache = {}
    @functools.wraps(func)
    def wrapper(n):
        if n not in _cache:
            _cache[n] = func(n)
        return _cache[n]
    return wrapper

@log_time
@cache
def slow_fib(n):
    if n <= 1:
        return n
    return slow_fib(n - 1) + slow_fib(n - 2)

print(slow_fib(30))    # 832040（有缓存很快）